Stock data prediction using predictive data mining techniques
- Author Heavendeep Kaur
- Co-Author Sandeep Kautish
- DOI
- Country : India
- Subject : CSE
Keywords : FPR, AUC, TPR, Data, Prediction
Abstract
Prediction system of stock market is very crucial and essentially important because it deals with the huge amount of money and in today’s growing and forward time, money is the first priority. The predicted value directly affects the stock price and no one take risk to drop down in stock market index. So due to money involvement and the reputation of the shares, stock market needs to be a perfect or more accurate prediction about their upcoming market trends. Various machine learning algorithms are used for stock data set and the objective is to predict the stock market. In this research work multiple learning algorithms with NN and ensembling methods are used to predict the data from unauthorized users. To calculate True positive rate (TPR), false positive rate (FPR), Area under the curve (AUC) and accuracy parameters and compare the previous result with new results.
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